python中基本类型的连接组合和互相转换

本篇总结了一下字符串，列表，字典，元组的连接组合使用和类型的互相转换小例子，尤其列表中的extend()方法和字典中的

update方法非常的常用。

1.连接两个字符串

a = "hello "
b = "world"
a += b
print(a)  # hello world

2.字典的连接

dict1 = {1: "a", 2: "b"}
dict2 = {3: "c", 4: "d"}
dict1.update(dict2)
print(dict1)  # {1: 'a', 2: 'b', 3: 'c', 4: 'd'}

3.列表的连接

list1 = [1, 2, 3]
list2 = [4, 5, 6]
list1.extend(list2)  # [1, 2, 3, 4, 5, 6]
print(list1)

4.元组的连接

tuple1 = (1, 2)
tuple2 = (3, 4)
tuple1 += tuple2
print(tuple1)  # (1, 2, 3, 4)

5.字典转换为字符串

dict1 = {1: "a", 2: "b"}
str1 = str(dict1)
print(str1)  # {1: 'a', 2: 'b'}
print(type(str1))  # <class 'str'>

6.字典转换为列表

dict1 = {1: "a", 2: "b"}
list1 = list(dict1.keys())
list2 = list(dict1.values())
list3 = list(dict1)
print(list1)  # [1, 2]
print(list2)  # ['a', 'b']
print(list3)  # [1,2]

7.字典转换为元组

dict1 = {1: "a", 2: "b"}
tuple1 = tuple(dict1.keys())
tuple2 = tuple(dict1.values())
tuple3 = tuple(dict1)
print(tuple1)  # (1, 2)
print(tuple2)  # ('a', 'b')
print(tuple3)  # (1, 2)

8.列表转换为字符串

list1 = [1, 2, 3]
str1 = str(list1)
print(str1)  # [1, 2, 3]
print(type(str1))  # <class 'str'>

9.列表转换为字典

# 1.
list1 = [1, 2, 3]
list2 = ["a", "b", "c"]
dict1 = dict(zip(list1, list2))
print(dict1)  # {1: 'a', 2: 'b', 3: 'c'}
# 2.
dict1 = {}
for i in list1:
    dict1[i] = list2[list1.index(i)]
print(dict1)  # {1: 'a', 2: 'b', 3: 'c'}
# 3.
list1 = [[1, 'a'], [2, 'b'], [3, 'c']]
dict1 = dict(list1)
print(dict1)  # {1: 'a', 2: 'b', 3: 'c'}

10.列表转换为元组

list1 = [1, 2, 3]
tuple1 = tuple(list1)
print(tuple1)  # (1, 2, 3)

11.元组转换为字符串

tuple1 = (1, 2, 3)
str1 = tuple(tuple1)
print(str1)  # (1, 2, 3)
print(type(str1))  # <class 'tuple'>

12.元组转换为字典

# 1.
tuple1 = (1, 2, 3)
tuple2 = (4, 5, 6)
dict1 = dict(zip(tuple1, tuple2))
print(dict1)  # {1: 4, 2: 5, 3: 6}
# 2
dict1 = {}
for i in tuple1:
    dict1[i] = tuple2[tuple1.index(i)]
print(dict1)  # {1: 4, 2: 5, 3: 6}

# 3
tuple1 = (1, 2)
tuple2 = (4, 5)
tuple3 = (tuple1, tuple2)
dict1 = dict(tuple3)
print(dict1)  # {1: 2, 4: 5}

 

13.元组转换为列表

tuple1 = (1, 2)
list1 = list(tuple1)
print(list1)  # [1, 2]